Influence functions related to eigenvalue problems which appear in multivariate analysis
- 1 January 1989
- journal article
- research article
- Published by Taylor & Francis in Communications in Statistics - Theory and Methods
- Vol. 18 (11) , 3991-4010
- https://doi.org/10.1080/03610928908830137
Abstract
Tanaka(1988) derived two influence functions related to an ordinary eigenvalue problem (A–λs I)vs = 0 of a real symmetric matrix A and used them for sensitivity analysis in principal component analysis. One of these influence functions was used to develop sensitivity analysis in factor analysis (see e.g. Tanaka and Odaka, 1988a). The present paper derives some additional influence functions related to an ordinary eigenvalue problem and also several influence functions related to a generalized eigenvalue problem (A–θs A)us = 0, where A and B are real symmetric and real symmetric positive definite matrices, respectively. These influence functions are applicable not only to the case where the eigenvalues of interest are all simple but also to the case where there are some multiple eigenvalues among those of interest.Keywords
This publication has 8 references indexed in Scilit:
- SENSITIVITY ANALYSIS IN PRINCIPAL COMPONENT REGRESSIONJapanese Journal of Biometrics, 1989
- Influential observations in principal component analysis:a case studyJournal of Applied Statistics, 1988
- Sensitivity analysis in principal component analysis:influence on the subspace spanned by principal components.Communications in Statistics - Theory and Methods, 1988
- Influence in principal components analysisBiometrika, 1985
- Multivariate ObservationsPublished by Wiley ,1984
- Influence functions for certain parameters in multivariate analysisCommunications in Statistics - Theory and Methods, 1981
- Studies in the Robustness of Multidimensional Scaling: Perturbational Analysis of Classical ScalingJournal of the Royal Statistical Society Series B: Statistical Methodology, 1979
- The Influence Curve and Its Role in Robust EstimationJournal of the American Statistical Association, 1974